Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Modeling within and between Sub-Genomes Epistasis of Synthetic Hexaploid Wheat for Genome-Enabled Prediction of Diseases.

Genes - 20 Feb 2024

Cuevas Jaime, González-Diéguez David, Dreisigacker Susanne, Martini Johannes W R, Crespo-Herrera Leo, Lozano-Ramirez Nerida, Singh Pawan K, He Xinyao, Huerta Julio, Crossa Jose

Abstract excerpt

Common wheat (Triticum aestivum) is a hexaploid crop comprising three diploid sub-genomes labeled A, B, and D. The objective of this study is to investigate whether there is a discernible influence pattern from the D sub-genome with epistasis in genomic models for wheat diseases. Four genomic statistical models were employed; two models considered the linear genomic relationship of the lines. The first model (G)...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Ascomycota
Share to Epistasis, Genetic

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Phenotype

Share to Triticum

Source

Open in PubMed Open full text

Identifiers

PMID: 38540321
DOI: 10.3390/genes15030262
PMCID: PMC10970072

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Modeling within and between Sub-Genomes Epistasis of Synthetic Hexaploid Wheat for Genome-Enabled Prediction of Diseases.PMID 38540321Read ↗

Improving genomic selection in hexaploid wheat with sub-genome additive and epistatic models.Semantic proximity Read ↗

Genomic prediction of synthetic hexaploid wheat upon tetraploid durum and diploid Aegilops parental pools.Semantic proximity Read ↗

Genomic Prediction of Resistance to Tan Spot, Spot Blotch and Septoria Nodorum Blotch in Synthetic Hexaploid Wheat.Semantic proximity Read ↗

Genomic regions conferring resistance to multiple fungal pathogens in synthetic hexaploid wheatSemantic proximity Read ↗

Genome-Wide Association Studies and Prediction of Tan Spot (Pyrenophoratritici-repentis) Infection in European Winter Wheat via Different Marker Platforms.Semantic proximity Read ↗

Genomic Prediction from Multi-Environment Trials of Wheat Breeding.Semantic proximity Read ↗

Using genomic selection to examine subgenome dominance and epistasis in allopolyploid strawberry.Semantic proximity Read ↗

Using genomic selection to examine subgenome dominance and epistasis in allopolyploid strawberrySemantic proximity Read ↗

Co-GWAS unveils the genetic architecture of inter-individual epistasis affecting biomass and disease severity in wheat binary mixturesSemantic proximity Read ↗

Phenotype Prediction Under Epistasis.Semantic proximity Read ↗

Capturing biological interactions improves predictive ability of complex traits via epistatic modelSemantic proximity Read ↗

Choosing the right tool: Leveraging of plant genetic resources in wheat (Triticum aestivum L.) benefits from selection of a suitable genomic prediction model.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.